%load_ext autoreload
%autoreload 2
hdma_path = "../../../"
hdma_chrombpnet_path = hdma_path + "output/03-chrombpnet/"
import sys
import h5py
import numpy as np
import pandas as pd
import logomaker
import os
# display all outputs in a cell
get_ipython().ast_node_interactivity = 'all'
This notebook loads the h5 file contained the combined/merged modisco patterns, filters out the ones that we have decided to drop after manual annotation, and then saves a new, filtered object to use downstream.
# first let's get the patterns to keep
patterns = pd.read_csv("04d-ChromBPNet_de_novo_motifs.tsv", sep="\t")
patterns.head()
| idx | pattern_class | pattern | total_n_seqlets | n_component_patterns | n_component_celltypes | n_component_organs | component_organs | component_celltypes | modisco_cwm_fwd | ... | match5 | qval5 | match6 | qval6 | match7 | qval7 | match8 | qval8 | match9 | qval9 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | pos | pos.Average_112__merged_pattern_0 | 192 | 5 | 5 | 3 | Brain,Lung,StomachEsophagus | dorsal radial glia,vascular endothelial,airway... | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 1 | 2 | pos | pos.Average_115__merged_pattern_0 | 105 | 2 | 2 | 2 | Lung,Skin | ciliated,fibroblast | NaN | ... | CTCFL: M08885_2.00 | 0.181525 | CTCFL: MA1102.2 | 0.181525 | CTCF: MA1929.1 | 0.181525 | CTCF: M07925_2.00 | 0.181525 | CTCF: M07863_2.00 | 0.181525 |
| 2 | 3 | pos | pos.Average_116__merged_pattern_0 | 47 | 2 | 2 | 2 | Muscle,Skin | smooth muscle,keratinocyte | NaN | ... | JDP2: M04292_2.00 | 0.047633 | CREB3L4: M04296_2.00 | 0.047633 | CREB3: M04241_2.00 | 0.047633 | CREM: M04229_2.00 | 0.047633 | CREB1: M04258_2.00 | 0.047633 |
| 3 | 4 | pos | pos.Average_131__merged_pattern_0 | 432 | 10 | 10 | 7 | Brain,Eye,Lung,Muscle,Skin,StomachEsophagus,Th... | excitatory neurons,trabecular meshwork,airway ... | NaN | ... | TP53: M09337_2.00 | 1.000000 | POU3F2: M05477_2.00 | 1.000000 | ZNF565: M07700_2.00 | 1.000000 | NRF1: M08177_2.00 | 1.000000 | NRF1: MA0506.1 | 1.000000 |
| 4 | 5 | pos | pos.Average_159__merged_pattern_0 | 535784 | 256 | 189 | 12 | Adrenal,Brain,Eye,Heart,Liver,Lung,Muscle,Skin... | adrenal cortex,excitatory neurons,dorsal radia... | NaN | ... | ZNF454: M04572_2.00 | 0.052145 | ZNF454: M04574_2.00 | 0.052145 | ZNF611: M07759_2.00 | 0.412382 | ZBTB14: M04631_2.00 | 0.451218 | ZBTB14: M04632_2.00 | 0.451218 |
5 rows × 45 columns
patterns = patterns[patterns.annotation != "drop"]
patterns_to_keep = patterns.pattern.values
len(patterns_to_keep)
patterns_to_keep[0:5]
742
array(['pos.Average_112__merged_pattern_0',
'pos.Average_115__merged_pattern_0',
'pos.Average_116__merged_pattern_0',
'pos.Average_131__merged_pattern_0',
'pos.Average_159__merged_pattern_0'], dtype=object)
compiled_h5 = hdma_chrombpnet_path + "02-compendium/modisco_compiled/modisco_compiled.h5"
filtered_h5 = hdma_chrombpnet_path + "02-compendium/modisco_compiled/modisco_compiled_filtered.h5"
# open the original HDF5 file in read mode and create a new HDF5 file in write mode
with h5.File(compiled_h5, "r") as old, h5.File(filtered_h5, "w") as new:
# iterate over the top-level groups (pos_patterns and neg_patterns)
for pattern_class in old.keys():
original_group = old[pattern_class]
# create the same structure in the new HDF5 file
new_group = new.create_group(pattern_class)
# only keep the specified patterns
for pattern in patterns_to_keep:
if pattern in original_group:
new_group.create_group(pattern)
new_group[pattern].create_dataset('contrib_scores', data=original_group[pattern]['contrib_scores'])
new_group[pattern].create_dataset('sequence', data=original_group[pattern]['sequence'])
new_group[pattern].create_dataset('hypothetical_contribs', data=original_group[pattern]['hypothetical_contribs'])
new_group[pattern].create_dataset('seqlets/n_seqlets', data=original_group[pattern]['seqlets/n_seqlets'])
print(f"Copied patterns to {pattern_class} in new HDF5 file: {list(new_group.keys())}")
<HDF5 group "/neg_patterns/neg.Average_12__merged_pattern_2" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Average_12__merged_pattern_3" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Average_12__merged_pattern_4" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Average_12__merged_pattern_5" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Average_12__merged_pattern_6" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Average_12__merged_pattern_7" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Average_12__merged_pattern_8" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Average_12__merged_pattern_12" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Average_12__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Average_12__merged_pattern_1" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Average_14__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Average_15__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Average_15__merged_pattern_1" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Average_16__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Average_16__merged_pattern_1" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Heart__Heart_c1__neg_patterns.pattern_0__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Heart__Heart_c3__neg_patterns.pattern_1__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Lung__Lung_c1__neg_patterns.pattern_0__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Thymus__Average_4__merged_pattern_2" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/neg_patterns/neg.Thymus__Average_6__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
Copied patterns to neg_patterns in new HDF5 file: ['neg.Average_12__merged_pattern_0', 'neg.Average_12__merged_pattern_1', 'neg.Average_12__merged_pattern_12', 'neg.Average_12__merged_pattern_2', 'neg.Average_12__merged_pattern_3', 'neg.Average_12__merged_pattern_4', 'neg.Average_12__merged_pattern_5', 'neg.Average_12__merged_pattern_6', 'neg.Average_12__merged_pattern_7', 'neg.Average_12__merged_pattern_8', 'neg.Average_14__merged_pattern_0', 'neg.Average_15__merged_pattern_0', 'neg.Average_15__merged_pattern_1', 'neg.Average_16__merged_pattern_0', 'neg.Average_16__merged_pattern_1', 'neg.Heart__Heart_c1__neg_patterns.pattern_0__merged_pattern_0', 'neg.Heart__Heart_c3__neg_patterns.pattern_1__merged_pattern_0', 'neg.Lung__Lung_c1__neg_patterns.pattern_0__merged_pattern_0', 'neg.Thymus__Average_4__merged_pattern_2', 'neg.Thymus__Average_6__merged_pattern_0']
<HDF5 group "/pos_patterns/pos.Average_112__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_115__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_116__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_131__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_159__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_159__merged_pattern_3" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_159__merged_pattern_5" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_159__merged_pattern_6" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_161__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_161__merged_pattern_1" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_161__merged_pattern_2" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_161__merged_pattern_3" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_161__merged_pattern_4" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_161__merged_pattern_5" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_161__merged_pattern_6" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_161__merged_pattern_7" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_303__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_190__merged_pattern_1" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_251__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_306__merged_pattern_1" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_303__merged_pattern_2" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_207__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_303__merged_pattern_3" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_207__merged_pattern_2" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_212__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_276__merged_pattern_5" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_303__merged_pattern_5" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_293__merged_pattern_0" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_294__merged_pattern_4" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_276__merged_pattern_8" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_306__merged_pattern_6" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
<HDF5 dataset "hypothetical_contribs": shape (30, 4), type "<f8">
<HDF5 dataset "n_seqlets": shape (1,), type "<i8">
<HDF5 group "/pos_patterns/pos.Average_212__merged_pattern_17" (0 members)>
<HDF5 dataset "contrib_scores": shape (30, 4), type "<f8">
<HDF5 dataset "sequence": shape (30, 4), type "<f8">
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'pos.Average_288__merged_pattern_2', 'pos.Average_288__merged_pattern_20', 'pos.Average_288__merged_pattern_21', 'pos.Average_288__merged_pattern_22', 'pos.Average_288__merged_pattern_23', 'pos.Average_288__merged_pattern_24', 'pos.Average_288__merged_pattern_25', 'pos.Average_288__merged_pattern_26', 'pos.Average_288__merged_pattern_27', 'pos.Average_288__merged_pattern_28', 'pos.Average_288__merged_pattern_29', 'pos.Average_288__merged_pattern_3', 'pos.Average_288__merged_pattern_30', 'pos.Average_288__merged_pattern_31', 'pos.Average_288__merged_pattern_32', 'pos.Average_288__merged_pattern_34', 'pos.Average_288__merged_pattern_35', 'pos.Average_288__merged_pattern_36', 'pos.Average_288__merged_pattern_37', 'pos.Average_288__merged_pattern_38', 'pos.Average_288__merged_pattern_39', 'pos.Average_288__merged_pattern_4', 'pos.Average_288__merged_pattern_40', 'pos.Average_288__merged_pattern_41', 'pos.Average_288__merged_pattern_42', 'pos.Average_288__merged_pattern_43', 'pos.Average_288__merged_pattern_5', 'pos.Average_288__merged_pattern_6', 'pos.Average_288__merged_pattern_7', 'pos.Average_288__merged_pattern_8', 'pos.Average_288__merged_pattern_9', 'pos.Average_289__merged_pattern_0', 'pos.Average_289__merged_pattern_1', 'pos.Average_290__merged_pattern_0', 'pos.Average_290__merged_pattern_1', 'pos.Average_290__merged_pattern_2', 'pos.Average_290__merged_pattern_3', 'pos.Average_290__merged_pattern_4', 'pos.Average_290__merged_pattern_5', 'pos.Average_291__merged_pattern_1', 'pos.Average_293__merged_pattern_0', 'pos.Average_293__merged_pattern_1', 'pos.Average_293__merged_pattern_2', 'pos.Average_293__merged_pattern_3', 'pos.Average_293__merged_pattern_4', 'pos.Average_293__merged_pattern_5', 'pos.Average_293__merged_pattern_6', 'pos.Average_293__merged_pattern_7', 'pos.Average_293__merged_pattern_9', 'pos.Average_294__merged_pattern_0', 'pos.Average_294__merged_pattern_1', 'pos.Average_294__merged_pattern_10', 'pos.Average_294__merged_pattern_12', 'pos.Average_294__merged_pattern_13', 'pos.Average_294__merged_pattern_14', 'pos.Average_294__merged_pattern_15', 'pos.Average_294__merged_pattern_16', 'pos.Average_294__merged_pattern_18', 'pos.Average_294__merged_pattern_19', 'pos.Average_294__merged_pattern_2', 'pos.Average_294__merged_pattern_20', 'pos.Average_294__merged_pattern_21', 'pos.Average_294__merged_pattern_22', 'pos.Average_294__merged_pattern_23', 'pos.Average_294__merged_pattern_25', 'pos.Average_294__merged_pattern_26', 'pos.Average_294__merged_pattern_27', 'pos.Average_294__merged_pattern_28', 'pos.Average_294__merged_pattern_29', 'pos.Average_294__merged_pattern_3', 'pos.Average_294__merged_pattern_30', 'pos.Average_294__merged_pattern_31', 'pos.Average_294__merged_pattern_32', 'pos.Average_294__merged_pattern_34', 'pos.Average_294__merged_pattern_35', 'pos.Average_294__merged_pattern_37', 'pos.Average_294__merged_pattern_38', 'pos.Average_294__merged_pattern_39', 'pos.Average_294__merged_pattern_4', 'pos.Average_294__merged_pattern_40', 'pos.Average_294__merged_pattern_5', 'pos.Average_294__merged_pattern_6', 'pos.Average_294__merged_pattern_7', 'pos.Average_294__merged_pattern_8', 'pos.Average_294__merged_pattern_9', 'pos.Average_295__merged_pattern_0', 'pos.Average_295__merged_pattern_1', 'pos.Average_295__merged_pattern_10', 'pos.Average_295__merged_pattern_11', 'pos.Average_295__merged_pattern_12', 'pos.Average_295__merged_pattern_13', 'pos.Average_295__merged_pattern_14', 'pos.Average_295__merged_pattern_15', 'pos.Average_295__merged_pattern_16', 'pos.Average_295__merged_pattern_17', 'pos.Average_295__merged_pattern_18', 'pos.Average_295__merged_pattern_19', 'pos.Average_295__merged_pattern_2', 'pos.Average_295__merged_pattern_20', 'pos.Average_295__merged_pattern_21', 'pos.Average_295__merged_pattern_22', 'pos.Average_295__merged_pattern_3', 'pos.Average_295__merged_pattern_4', 'pos.Average_295__merged_pattern_5', 'pos.Average_295__merged_pattern_6', 'pos.Average_295__merged_pattern_7', 'pos.Average_295__merged_pattern_8', 'pos.Average_295__merged_pattern_9', 'pos.Average_296__merged_pattern_0', 'pos.Average_296__merged_pattern_1', 'pos.Average_296__merged_pattern_10', 'pos.Average_296__merged_pattern_11', 'pos.Average_296__merged_pattern_12', 'pos.Average_296__merged_pattern_2', 'pos.Average_296__merged_pattern_3', 'pos.Average_296__merged_pattern_4', 'pos.Average_296__merged_pattern_5', 'pos.Average_296__merged_pattern_7', 'pos.Average_296__merged_pattern_8', 'pos.Average_296__merged_pattern_9', 'pos.Average_301__merged_pattern_0', 'pos.Average_303__merged_pattern_0', 'pos.Average_303__merged_pattern_1', 'pos.Average_303__merged_pattern_10', 'pos.Average_303__merged_pattern_11', 'pos.Average_303__merged_pattern_12', 'pos.Average_303__merged_pattern_13', 'pos.Average_303__merged_pattern_14', 'pos.Average_303__merged_pattern_15', 'pos.Average_303__merged_pattern_16', 'pos.Average_303__merged_pattern_17', 'pos.Average_303__merged_pattern_18', 'pos.Average_303__merged_pattern_19', 'pos.Average_303__merged_pattern_2', 'pos.Average_303__merged_pattern_20', 'pos.Average_303__merged_pattern_21', 'pos.Average_303__merged_pattern_22', 'pos.Average_303__merged_pattern_23', 'pos.Average_303__merged_pattern_24', 'pos.Average_303__merged_pattern_25', 'pos.Average_303__merged_pattern_26', 'pos.Average_303__merged_pattern_27', 'pos.Average_303__merged_pattern_28', 'pos.Average_303__merged_pattern_29', 'pos.Average_303__merged_pattern_3', 'pos.Average_303__merged_pattern_30', 'pos.Average_303__merged_pattern_31', 'pos.Average_303__merged_pattern_34', 'pos.Average_303__merged_pattern_35', 'pos.Average_303__merged_pattern_37', 'pos.Average_303__merged_pattern_38', 'pos.Average_303__merged_pattern_4', 'pos.Average_303__merged_pattern_40', 'pos.Average_303__merged_pattern_41', 'pos.Average_303__merged_pattern_42', 'pos.Average_303__merged_pattern_43', 'pos.Average_303__merged_pattern_44', 'pos.Average_303__merged_pattern_45', 'pos.Average_303__merged_pattern_46', 'pos.Average_303__merged_pattern_47', 'pos.Average_303__merged_pattern_48', 'pos.Average_303__merged_pattern_49', 'pos.Average_303__merged_pattern_5', 'pos.Average_303__merged_pattern_50', 'pos.Average_303__merged_pattern_51', 'pos.Average_303__merged_pattern_52', 'pos.Average_303__merged_pattern_53', 'pos.Average_303__merged_pattern_54', 'pos.Average_303__merged_pattern_55', 'pos.Average_303__merged_pattern_57', 'pos.Average_303__merged_pattern_58', 'pos.Average_303__merged_pattern_6', 'pos.Average_303__merged_pattern_60', 'pos.Average_303__merged_pattern_61', 'pos.Average_303__merged_pattern_62', 'pos.Average_303__merged_pattern_7', 'pos.Average_303__merged_pattern_8', 'pos.Average_303__merged_pattern_9', 'pos.Average_305__merged_pattern_0', 'pos.Average_305__merged_pattern_1', 'pos.Average_305__merged_pattern_12', 'pos.Average_305__merged_pattern_13', 'pos.Average_305__merged_pattern_14', 'pos.Average_305__merged_pattern_2', 'pos.Average_305__merged_pattern_6', 'pos.Average_305__merged_pattern_8', 'pos.Average_305__merged_pattern_9', 'pos.Average_306__merged_pattern_0', 'pos.Average_306__merged_pattern_1', 'pos.Average_306__merged_pattern_10', 'pos.Average_306__merged_pattern_100', 'pos.Average_306__merged_pattern_101', 'pos.Average_306__merged_pattern_11', 'pos.Average_306__merged_pattern_12', 'pos.Average_306__merged_pattern_13', 'pos.Average_306__merged_pattern_14', 'pos.Average_306__merged_pattern_15', 'pos.Average_306__merged_pattern_16', 'pos.Average_306__merged_pattern_17', 'pos.Average_306__merged_pattern_18', 'pos.Average_306__merged_pattern_19', 'pos.Average_306__merged_pattern_2', 'pos.Average_306__merged_pattern_20', 'pos.Average_306__merged_pattern_21', 'pos.Average_306__merged_pattern_22', 'pos.Average_306__merged_pattern_23', 'pos.Average_306__merged_pattern_24', 'pos.Average_306__merged_pattern_25', 'pos.Average_306__merged_pattern_27', 'pos.Average_306__merged_pattern_28', 'pos.Average_306__merged_pattern_29', 'pos.Average_306__merged_pattern_3', 'pos.Average_306__merged_pattern_30', 'pos.Average_306__merged_pattern_31', 'pos.Average_306__merged_pattern_32', 'pos.Average_306__merged_pattern_33', 'pos.Average_306__merged_pattern_35', 'pos.Average_306__merged_pattern_36', 'pos.Average_306__merged_pattern_37', 'pos.Average_306__merged_pattern_38', 'pos.Average_306__merged_pattern_39', 'pos.Average_306__merged_pattern_4', 'pos.Average_306__merged_pattern_40', 'pos.Average_306__merged_pattern_41', 'pos.Average_306__merged_pattern_42', 'pos.Average_306__merged_pattern_43', 'pos.Average_306__merged_pattern_45', 'pos.Average_306__merged_pattern_46', 'pos.Average_306__merged_pattern_47', 'pos.Average_306__merged_pattern_48', 'pos.Average_306__merged_pattern_49', 'pos.Average_306__merged_pattern_5', 'pos.Average_306__merged_pattern_50', 'pos.Average_306__merged_pattern_51', 'pos.Average_306__merged_pattern_52', 'pos.Average_306__merged_pattern_54', 'pos.Average_306__merged_pattern_56', 'pos.Average_306__merged_pattern_57', 'pos.Average_306__merged_pattern_58', 'pos.Average_306__merged_pattern_59', 'pos.Average_306__merged_pattern_6', 'pos.Average_306__merged_pattern_60', 'pos.Average_306__merged_pattern_62', 'pos.Average_306__merged_pattern_63', 'pos.Average_306__merged_pattern_65', 'pos.Average_306__merged_pattern_66', 'pos.Average_306__merged_pattern_67', 'pos.Average_306__merged_pattern_69', 'pos.Average_306__merged_pattern_7', 'pos.Average_306__merged_pattern_70', 'pos.Average_306__merged_pattern_71', 'pos.Average_306__merged_pattern_72', 'pos.Average_306__merged_pattern_76', 'pos.Average_306__merged_pattern_77', 'pos.Average_306__merged_pattern_78', 'pos.Average_306__merged_pattern_79', 'pos.Average_306__merged_pattern_8', 'pos.Average_306__merged_pattern_80', 'pos.Average_306__merged_pattern_82', 'pos.Average_306__merged_pattern_83', 'pos.Average_306__merged_pattern_84', 'pos.Average_306__merged_pattern_85', 'pos.Average_306__merged_pattern_86', 'pos.Average_306__merged_pattern_87', 'pos.Average_306__merged_pattern_88', 'pos.Average_306__merged_pattern_89', 'pos.Average_306__merged_pattern_9', 'pos.Average_306__merged_pattern_90', 'pos.Average_306__merged_pattern_91', 'pos.Average_306__merged_pattern_92', 'pos.Average_306__merged_pattern_93', 'pos.Average_306__merged_pattern_94', 'pos.Average_306__merged_pattern_95', 'pos.Average_306__merged_pattern_96', 'pos.Average_306__merged_pattern_97', 'pos.Average_306__merged_pattern_98', 'pos.Average_306__merged_pattern_99', 'pos.Average_30__merged_pattern_0', 'pos.Average_64__merged_pattern_0', 'pos.Average_73__merged_pattern_0', 'pos.Average_80__merged_pattern_0', 'pos.Average_80__merged_pattern_1', 'pos.Average_85__merged_pattern_0', 'pos.Average_85__merged_pattern_1', 'pos.Average_85__merged_pattern_10', 'pos.Average_85__merged_pattern_11', 'pos.Average_85__merged_pattern_2', 'pos.Average_85__merged_pattern_3', 'pos.Average_85__merged_pattern_4', 'pos.Average_85__merged_pattern_5', 'pos.Average_85__merged_pattern_6', 'pos.Average_85__merged_pattern_7', 'pos.Average_85__merged_pattern_8', 'pos.Average_85__merged_pattern_9', 'pos.Brain__Average_327__merged_pattern_0', 'pos.Brain__Brain_c6__pos_patterns.pattern_25__merged_pattern_0', 'pos.Eye__Average_488__merged_pattern_0', 'pos.Eye__Average_488__merged_pattern_1', 'pos.Eye__Average_488__merged_pattern_2', 'pos.Eye__Eye_c11__pos_patterns.pattern_18__merged_pattern_0', 'pos.Eye__Eye_c14__pos_patterns.pattern_14__merged_pattern_0', 'pos.Eye__Eye_c1__pos_patterns.pattern_37__merged_pattern_0', 'pos.Eye__Eye_c8__pos_patterns.pattern_22__merged_pattern_0', 'pos.Heart__Average_290__merged_pattern_0', 'pos.Heart__Average_368__merged_pattern_0', 'pos.Heart__Average_396__merged_pattern_0', 'pos.Heart__Heart_c0__pos_patterns.pattern_35__merged_pattern_0', 'pos.Heart__Heart_c0__pos_patterns.pattern_38__merged_pattern_0', 'pos.Heart__Heart_c2__pos_patterns.pattern_34__merged_pattern_0', 'pos.Liver__Average_285__merged_pattern_0', 'pos.Liver__Average_401__merged_pattern_0', 'pos.Liver__Average_407__merged_pattern_0', 'pos.Liver__Average_407__merged_pattern_1', 'pos.Liver__Average_439__merged_pattern_0', 'pos.Liver__Average_439__merged_pattern_1', 'pos.Liver__Average_46__merged_pattern_0', 'pos.Liver__Average_478__merged_pattern_2', 'pos.Liver__Liver_c0__pos_patterns.pattern_26__merged_pattern_0', 'pos.Liver__Liver_c11__pos_patterns.pattern_27__merged_pattern_0', 'pos.Liver__Liver_c1__pos_patterns.pattern_38__merged_pattern_0', 'pos.Liver__Liver_c4__pos_patterns.pattern_42__merged_pattern_0', 'pos.Liver__Liver_c5__pos_patterns.pattern_20__merged_pattern_0', 'pos.Lung__Lung_c0__pos_patterns.pattern_51__merged_pattern_0', 'pos.Lung__Lung_c11__pos_patterns.pattern_40__merged_pattern_0', 'pos.Lung__Lung_c4__pos_patterns.pattern_36__merged_pattern_0', 'pos.Muscle__Muscle_c18__pos_patterns.pattern_24__merged_pattern_0', 'pos.Skin__Average_96__merged_pattern_0', 'pos.Skin__Skin_c0__pos_patterns.pattern_37__merged_pattern_0', 'pos.Skin__Skin_c0__pos_patterns.pattern_44__merged_pattern_0', 'pos.Skin__Skin_c17__pos_patterns.pattern_23__merged_pattern_0', 'pos.Skin__Skin_c18__pos_patterns.pattern_25__merged_pattern_0', 'pos.Skin__Skin_c2__pos_patterns.pattern_45__merged_pattern_0', 'pos.Skin__Skin_c3__pos_patterns.pattern_34__merged_pattern_0', 'pos.Skin__Skin_c7__pos_patterns.pattern_42__merged_pattern_0', 'pos.Skin__Skin_c9__pos_patterns.pattern_24__merged_pattern_0', 'pos.Spleen__Average_288__merged_pattern_0', 'pos.Spleen__Average_288__merged_pattern_1', 'pos.Spleen__Average_367__merged_pattern_0', 'pos.Spleen__Average_367__merged_pattern_1', 'pos.Spleen__Average_367__merged_pattern_2', 'pos.Spleen__Average_399__merged_pattern_0', 'pos.Spleen__Average_399__merged_pattern_1', 'pos.Spleen__Average_399__merged_pattern_2', 'pos.Spleen__Average_402__merged_pattern_0', 'pos.Spleen__Average_402__merged_pattern_1', 'pos.Spleen__Average_402__merged_pattern_2', 'pos.Spleen__Spleen_c3__pos_patterns.pattern_40__merged_pattern_0', 'pos.Stomach__Average_553__merged_pattern_0', 'pos.Stomach__Average_553__merged_pattern_1', 'pos.Stomach__Average_553__merged_pattern_2', 'pos.Stomach__Stomach_c3__pos_patterns.pattern_29__merged_pattern_0', 'pos.Thymus__Average_257__merged_pattern_0', 'pos.Thymus__Thymus_c2__pos_patterns.pattern_38__merged_pattern_0', 'pos.Thymus__Thymus_c6__pos_patterns.pattern_44__merged_pattern_0', 'pos.Thyroid__Thyroid_c2__pos_patterns.pattern_17__merged_pattern_0', 'pos.Thyroid__Thyroid_c2__pos_patterns.pattern_20__merged_pattern_0', 'pos.Thyroid__Thyroid_c2__pos_patterns.pattern_27__merged_pattern_0', 'pos.Thyroid__Thyroid_c2__pos_patterns.pattern_33__merged_pattern_0']
# check that this looks correct
modisco_obj = h5py.File(filtered_h5)
modisco_obj['neg_patterns'].keys()
<KeysViewHDF5 ['neg.Average_12__merged_pattern_0', 'neg.Average_12__merged_pattern_1', 'neg.Average_12__merged_pattern_12', 'neg.Average_12__merged_pattern_2', 'neg.Average_12__merged_pattern_3', 'neg.Average_12__merged_pattern_4', 'neg.Average_12__merged_pattern_5', 'neg.Average_12__merged_pattern_6', 'neg.Average_12__merged_pattern_7', 'neg.Average_12__merged_pattern_8', 'neg.Average_14__merged_pattern_0', 'neg.Average_15__merged_pattern_0', 'neg.Average_15__merged_pattern_1', 'neg.Average_16__merged_pattern_0', 'neg.Average_16__merged_pattern_1', 'neg.Heart__Heart_c1__neg_patterns.pattern_0__merged_pattern_0', 'neg.Heart__Heart_c3__neg_patterns.pattern_1__merged_pattern_0', 'neg.Lung__Lung_c1__neg_patterns.pattern_0__merged_pattern_0', 'neg.Thymus__Average_4__merged_pattern_2', 'neg.Thymus__Average_6__merged_pattern_0']>
len(modisco_obj['pos_patterns'].keys())
722
modisco_obj['pos_patterns']['pos.Average_306__merged_pattern_1'].keys()
modisco_obj['pos_patterns']['pos.Average_306__merged_pattern_1']['contrib_scores'][()]
<KeysViewHDF5 ['contrib_scores', 'hypothetical_contribs', 'seqlets', 'sequence']>
array([[ 2.00078729e-04, 1.70384791e-03, 1.81830139e-03,
9.78267330e-04],
[ 1.40478319e-04, 1.87089228e-03, 1.63095215e-03,
5.76457694e-04],
[ 3.71845924e-04, 1.69704266e-03, 1.39124971e-03,
3.71816120e-04],
[ 3.22040375e-04, 1.82450780e-03, 1.16445869e-03,
2.92751667e-04],
[ 1.88725173e-04, 1.53890373e-03, 1.82179265e-03,
2.20935600e-04],
[ 2.88312844e-04, 1.69269347e-03, 1.42139359e-03,
3.32037009e-04],
[ 1.42745808e-04, 2.55045541e-03, 1.44968094e-03,
1.76880952e-04],
[ 8.03297423e-05, 3.49916901e-03, 1.31478131e-03,
1.15046789e-04],
[ 4.29160424e-05, 2.06061506e-03, 2.73937683e-03,
1.55560233e-04],
[ 5.55070226e-04, 1.72968612e-03, 2.07557653e-03,
5.30906048e-05],
[ 1.21241542e-03, 1.60212766e-03, 1.63825684e-03,
4.64105882e-04],
[ 2.90039258e-03, 1.44333084e-04, 3.09838109e-03,
9.89847823e-05],
[ 2.69102937e-04, 1.05289221e-02, 1.65229799e-03,
-1.30774067e-04],
[ 7.43077016e-04, 3.36849112e-02, 1.44172823e-04,
1.53458800e-05],
[ 2.08284587e-05, 1.53418604e-05, 4.32381923e-02,
8.84491262e-06],
[ 1.54693320e-05, 1.11724344e-04, 2.74586877e-02,
1.83708420e-04],
[ 3.32692102e-02, 1.07681258e-04, 3.75646685e-05,
2.37408508e-05],
[ 2.70994159e-02, 3.14824792e-04, 3.05554247e-05,
2.80412253e-04],
[ 1.94685782e-03, 5.88078006e-05, 1.64610134e-02,
5.47993869e-05],
[ 5.27928325e-05, 5.62439655e-04, 6.01804498e-05,
3.03711418e-02],
[ 1.65872330e-04, 4.39430024e-04, 1.37029657e-02,
8.81986235e-04],
[ 1.97750323e-02, 9.65067334e-04, 1.20819694e-03,
-4.29877983e-05],
[ 8.05529772e-06, 3.42502448e-02, 5.33737974e-05,
3.28393267e-05],
[ 4.60302826e-06, -3.85857062e-06, 3.17068419e-02,
9.23673404e-05],
[-9.76422070e-05, 4.33469962e-03, 4.40598164e-04,
8.39419833e-03],
[ 3.00504605e-03, 3.17740643e-03, 1.52490681e-03,
1.94314524e-04],
[ 5.24081930e-03, 7.81684468e-04, 4.31379699e-04,
5.10767641e-04],
[ 7.06055171e-05, 2.06860948e-03, 8.11902987e-04,
1.14729312e-03],
[ 4.47510427e-04, 1.97235641e-03, 1.70981604e-03,
4.24550367e-04],
[ 9.38479354e-05, 1.82544780e-03, 2.07513929e-03,
4.03103897e-04]])
df1 = pd.DataFrame(modisco_obj['pos_patterns']['pos.Average_306__merged_pattern_1']['contrib_scores'], columns=["A", "C", "G", "T"])
logo1 = logomaker.Logo(df1)
logo1.style_spines(visible=False)
logo1.ax.set_ylabel("Contrib (CWM)", labelpad=-1)
Text(0, 0.5, 'Contrib (CWM)')
